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Hrishikesh Raghunath
Mid-level Data Engineer specializing in scalable ETL, streaming analytics, and cloud data platforms
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At Dreamline AI, built and productionized an AWS-based incentive intelligence platform that uses Llama-2/GPT-4 to extract eligibility rules from unstructured state policy documents into structured JSON, then processes them with Glue/PySpark and serves results via Lambda/SageMaker/API Gateway. Designed state-specific ingestion connectors plus schema validation and automated checks/alerts to handle frequent policy/format changes without breaking the pipeline, and partnered with business/analytics stakeholders to deliver interpretable eligibility decisions via explanations and dashboards.
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Key Strengths
- Built and deployed an LLM-powered incentive eligibility system to production on AWS
- Structured unstructured policy documents into JSON using Llama-2/GPT-4 for downstream analytics
- Designed resilient ingestion connectors per state to prevent pipeline breakage from policy/format changes
- Implemented schema validation and automated checks/alerts to detect new/missing fields and format changes
- End-to-end ETL orchestration with Airflow (DAG visibility, retries, dependency management, data availability checks)
- Combined gradient boosting eligibility modeling with LLM-generated explanations for interpretability
- Practical evaluation and reliability approach (unit tests, simulations, end-to-end testing, monitoring for drift/latency)
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